Foundations of the Pareto Iterated Local Search Metaheuristic
| dc.creator | Geiger, Martin Josef | |
| dc.date | 2008-09-02 | |
| dc.date.accessioned | 2026-07-07T09:59:58Z | |
| dc.date.available | 2026-07-07T09:59:58Z | |
| dc.description | The paper describes the proposition and application of a local search metaheuristic for multi-objective optimization problems. It is based on two main principles of heuristic search, intensification through variable neighborhoods, and diversification through perturbations and successive iterations in favorable regions of the search space. The concept is successfully tested on permutation flow shop scheduling problems under multiple objectives. While the obtained results are encouraging in terms of their quality, another positive attribute of the approach is its' simplicity as it does require the setting of only very few parameters. The implementation of the Pareto Iterated Local Search metaheuristic is based on the MOOPPS computer system of local search heuristics for multi-objective scheduling which has been awarded the European Academic Software Award 2002 in Ronneby, Sweden (http://www.easa-award.net/, http://www.bth.se/llab/easa_2002.nsf) | |
| dc.description | Proceedings of the 18th International Conference on Multiple Criteria Decision Making, Chania, Greece, June 19-23, 2006 | |
| dc.identifier | https://arxiv.org/abs/0809.0406 | |
| dc.identifier | http://arxiv.org/abs/0809.0406 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/168215 | |
| dc.subject | Artificial Intelligence | |
| dc.title | Foundations of the Pareto Iterated Local Search Metaheuristic | |
| dc.type | text |